The authors have proposed a new type of flexible and printable 12GHz-band phase shifter using polymer actuator for the first time. Polymer bending actuator was used as a termination device of a reflection-type 3-dB, 90° hybrid coupler as the phase-shift control unit which controls the electrical length of the waveguide for microwave signals by the applied bias voltage. The microstrip line circuit of the device has been fabricated using low-cost screen printing method. Polymer bending actuator having three-layer stacking structure, in which an ionic liquid electrolyte layer is sandwiched with two conductive network composite layers, was formed by wet processes. The authors have confirmed that the phase shift could be controlled in analog by low driving voltages of 2-7 V for the actuator with a insertion loss of 2.73 dB. This phase shifter can be integrated with flexible patch antenna and the current flexible polymer electronics devices such as transistors.

A wind-noise suppressor with SNR based wind-noise detection and speech-wind discrimination is proposed. Wind-noise detection is performed in each frame and frequency based on the power ratio of the noisy speech and an estimated stationary noise. The detection result is modified by speech presence likelihood representing spectral smoothness to eliminate speech components. To suppress wind noise with little speech distortion, spectral gains are made smaller in the frame and the frequency where wind-noise is detected. Subjective evaluation results show that the 5-grade MOS for the proposed wind-noise suppressor reaches 3.4 and is 0.56 higher than that by a conventional noise suppressor with a statistically significant difference.

The Jacobi-Davidson method and the Riccati method for eigenvalue problems are studied. In the methods, one has to solve a nonlinear equation called the correction equation per iteration, and the difference between the methods comes from how to solve the equation. In the Jacobi-Davidson/Riccati method the correction equation is solved with/without linearization. In the literature, avoiding the linearization is known as an improvement to get a better solution of the equation and bring the faster convergence. In fact, the Riccati method showed superior convergence behavior for some problems. Nevertheless the advantage of the Riccati method is still unclear, because the correction equation is solved not exactly but with low accuracy. In this paper, we analyzed the approximate solution of the correction equation and clarified the point that the Riccati method is specialized for computing particular solutions of eigenvalue problems. The result suggests that the two methods should be selectively used depending on target solutions. Our analysis was verified by numerical experiments.

This letter proposes a track before detect scheme embedded in coherent repeated interference with the aid of frequency diversity array. The unmatched properties between echo and interferences are firstly discussed from both signal processing and data processing standpoints. Afterward, the interference suppression algorithm with virtual channel weighting at continue sampling stage is proposed, followed with kinematics constraint correspondingly. Further, the evaluations of the interference suppression performance are carried out through simulations which illustrate the feasibility and validity of the proposed algorithm.

Zero-difference balanced (ZDB) functions, which have many applications in coding theory and sequence design, have received a lot of attention in recent years. In this letter, based on two known classes of ZDB functions, a new class of ZDB functions, which is defined on the group (Z2e-1×Zn,+) is presented, where e is a prime and n=p1m1p2m2…pkmk, pi is odd prime satisfying that e|(pi-1) for any 1≤i≤k . In the case of gcd(2e-1,n)=1, the new constructed ZDB functions are cyclic.

To track the players and shuttlecock in broadcast badminton video is a challenge, especially for tracking the small size and fast moving shuttlecock. There are many situations that may cause occlusion or misdetection. In this paper, a method is proposed to track players and shuttlecock in broadcast badminton videos. We apply adaptive Kalman filter, trajectory confidence estimation and confidence-update (Location Similarity and Relative Motion Relation, RMR) to improve the accuracy of object trajectories. In our experiments, the proposed method significantly enhance the tracking success rate of players and shuttlecock.

Location information is essential to varieties of applications. It is one of the most important context to be detected by wireless distributed sensors, which is a key technology in Internet-of-Things. Fingerprint-based methods, which compare location unique fingerprints collected beforehand with the fingerprint measured from the target, have attracted much attention recently in both of academia and industry. They have been successfully used for many location-based applications. From the viewpoint of practical applications, in this paper, four different typical approaches of fingerprint-based radio emitter localization system are introduced with four different representative applications: localization of LTE smart phone used for anti-cheating in exams, indoor localization of Wi-Fi terminals, localized light control in BEMS using location information of occupants, and illegal radio localization in outdoor environments. Based on the different practical application scenarios, different solutions, which are designed to enhance the localization performance, are discussed in detail. To the best of the authors' knowledge, this is the first paper to give a guideline for readers about fingerprint-based localization system in terms of fingerprint selection, hardware architecture design and algorithm enhancement.

As one functionality of the wireless distributed network (WDN) enabling flexible wireless networks, it is supposed that a dynamic spectrum access is applied to OFDM systems for superior radio resource management. As a basic technology for such WDN, our study deals with the OFDM signal detection based on its cyclostationary feature. Previous relevant studies mainly relied on software simulations based on the Monte Carlo method. This paper analytically clarifies the relationship between the design parameters of the detector and its detection performance. The detection performance is formulated by using multiple design parameters including the transfer function of the receive filter. A hardware experiment with radio frequency (RF) signals is also carried out by using the detector consisting of an RF unit and FPGA. Thereby, it is verified that the detection characteristics represented by the false-alarm and non-detection probabilities calculated by the analytical formula agree well with those obtained by the hardware experiment. Our analysis and experiment results are useful for the parameter design of the signal detector to satisfy required performance criteria.

Spectrum databases are required to assist the process of radio propagation estimation for spectrum sharing. Especially, a measurement-based spectrum database achieves highly efficient spectrum sharing by storing the observed radio environment information such as the signal power transmitted from a primary user. However, when the average received signal power is calculated in a given square mesh, the bias of the observation locations within the mesh strongly degrades the accuracy of the statistics because of the influence of terrain and buildings. This paper proposes a method for determining the statistics by using mesh clustering. The proposed method clusters the feature vectors of the measured data by using the k-means and Gaussian mixture model methods. Simulation results show that the proposed method can decrease the error between the measured value and the statistically processed value even if only a small amount of data is available in the spectrum database.

IEEE 802.11ah is a specification being developed for sub-1GHz license-exempt operation and is intended to provide Low Power Wide Area (LPWA) communication services and support Internet of Things (IoT) features such as large-scale networks and extended transmission range. However, these features also make the 802.11ah networks highly susceptible to channel contention and hidden node problem (HNP). To address the problems, the 11ah Task Group proposed a Restricted Access Window (RAW) mechanism. It shows outstanding performance in alleviating channel contention, but its effect on solving HNP is unsatisfactory. In this paper, we propose a simple and effective hidden node grouping algorithm (HNGA) based on IEEE 802.11ah RAW. The algorithm collects hidden node information by taking advantage of the 802.11 association process and then performs two-stage uniform grouping to prevent hidden node collisions (HNCs). Performance of the proposed algorithm is evaluated in comparison with other existing schemes in a hidden node situation. The results show that our proposed algorithm eliminates most of hidden node pairs inside a RAW group with low overhead penalty, thereby improving the performance of the network. Moreover, the algorithm is immune to HNCs caused by cross slot boundary transmissions.

After large-scale disasters, information sharing among people becomes more important than usual. This, however, is extremely difficult to achieve in disaster zones due to serious damage to the existing network infrastructure, power outages, and high traffic congestion. For the quick provision of alternative networks to serve heavy communication demands after disasters, establishing local area networks (LANs) consisting of portable servers with data storage has been considered as one of the most promising solutions. Based on the established LAN and a data server in each area, people can share many kinds of disaster-related information such as emergency information and supply/demand information via deployed neighboring servers. However, due to the lack of stable Internet connection, these servers are isolated and cannot be synchronized in real time. To enable and guarantee more efficient information sharing across the whole disaster-hit area, data stored on each server should be synchronized without the Internet. Our solution is to propose an intermittent data synchronization scheme that uses moving vehicles as relays to exchange data between isolated servers after disasters. With the objective of maximizing the total number of synchronized high priority data under the capability constraints of mobile relays, we first propose a data allocation scheme (DAS) from a server to a mobile relay. After that, we propose a trajectory planning scheme for the relays which is formulated as a Mixed Integer Linear Fractional Programming (MILFP) problem, and an algorithm to solve it efficiently. Extensive simulations and comparisons with other methods show the superior performance of our proposals.

For more flexible and efficient use of radio spectrum, reconfigurable RF devices have important roles in the future wireless systems. In 5G mobile communications, concurrent multi-band operation using new SHF bands is considered. This paper presents a new configuration of dual-band SHF BPF consisting of a low SHF three-bit reconfigurable BPF and a high SHF BPF. The proposed dual-band BPF employs direct parallel connection without additional divider/combiner to reduce circuit elements and simplify the BPF. In order to obtain a good isolation between two passbands while achieving a wide center frequency range in the low SHF BPF, input/output impedances and external Qs of BPFs are analyzed and feedbacked to the design. A high SHF BPF design method with tapped transmission line resonators and lumped-element coupling is also presented to make the BPF compact. Two types of prototypes; all inductor-coupled dual-band BPF and C-L-C coupled dual-band BPF were designed and fabricated. Both prototypes have low SHF reconfigurable center frequency range from 3.5 to 5 GHz as well as high SHF center frequency of 8.5 GHz with insertion loss below 2.0 dB.

Spectrum-based fault localization (SFL) is a lightweight approach, which aims at helping debuggers to identity root causes of failures by measuring suspiciousness for each program component being a fault, and generate a hypothetical fault ranking list. Although SFL techniques have been shown to be effective, the fault component in a buggy program cannot always be ranked at the top due to its complex fault triggering models. However, it is extremely difficult to model the complex triggering models for all buggy programs. To solve this issue, we propose two simple fault triggering models (RIPRα and RIPRβ), and a refinement technique to improve fault absolute ranking based on the two fault triggering models, through ruling out some higher ranked components according to its fault triggering model. Intuitively, our approach is effective if a fault component was ranked within top k in the two fault ranking lists outputted by the two fault localization strategies. Experimental results show that our approach can significantly improve the fault absolute ranking in the three cases.

In general, effective integrating the advantages of different trackers can achieve unified performance promotion. In this work, we study the integration of multiple correlation filter (CF) trackers; propose a novel but simple tracking integration method that combines different trackers in filter level. Due to the variety of their correlation filter and features, there is no comparability between different CF tracking results for tracking integration. To tackle this, we propose twofold CF to unify these various response maps so that the results of different tracking algorithms can be compared, so as to boost the tracking performance like ensemble learning. Experiment of two CF methods integration on the data sets OTB demonstrates that the proposed method is effective and promising.

This paper presents the design of a capacitive coupler for underwater wireless power transfer (U-WPT) focusing on kQ product. Power transfer efficiency hinges on the coupling coefficient k between the couplers and Q-factor of water calculated from the complex permittivity. High efficiency can be achieved by handling k and the Q-factor effectively. First, the pivotal elements on k are derived from the equivalent circuit of the coupler. Next, the frequency characteristic of the Q-factor in tap water is calculated from the measured results. Then, the design parameters in which kQ product has the maximal values are determined. Finally, it is demonstrated that the efficiency of U-WPT with the capacitive coupling designed by our method achieves approximately 80%.

This paper mainly discusses the time-difference-of-arrival (TDOA) estimation problem of digital modulation signal under impulsive noise and cochannel interference environment. Since the conventional TDOA estimation algorithms based on the second-order cyclic statistics degenerate severely in impulsive noise and the TDOA estimation algorithms based on correntropy are out of work in cochannel interference, a novel signal-selective algorithm based on the generalized cyclic correntropy is proposed, which can suppress both impulsive noise and cochannel interference. Theoretical derivation and simulation results demonstrate the effectiveness and robustness of the proposed algorithm.

We numerically simulated electrical properties, i.e., the resistance and Coulomb blockade threshold, of randomly-placed conductive nanoparticles. In simulation, tunnel junctions were assumed to be formed between neighboring particle-particle and particle-electrode connections. On a plane of triangle 100×100 grids, three electrodes, the drain, source, and gate, were defined. After random placements of conductive particles, the connection between the drain and source electrodes were evaluated with keeping the gate electrode disconnected. The resistance was obtained by use of a SPICE-like simulator, whereas the Coulomb blockade threshold was determined from the current-voltage characteristics simulated using a Monte-Carlo simulator. Strong linear correlation between the resistance and threshold voltage was confirmed, which agreed with results for uniform one-dimensional arrays.

In compressed sensing, most previous researches have studied the recovery performance of a sparse signal x based on the acquired model y=Φx+n, where n denotes the noise vector. There are also related studies for general perturbation environment, i.e., y=(Φ+E)x+n, where E is the measurement perturbation. IHT and HTP algorithms are the classical algorithms for sparse signal reconstruction in compressed sensing. Under the general perturbations, this paper derive the required sufficient conditions and the error bounds of IHT and HTP algorithms.

Recently, multi-issue closed negotiations have attracted attention in multi-agent systems. In particular, multi-time and multilateral negotiation strategies are important topics in multi-issue closed negotiations. In multi-issue closed negotiations, an automated negotiating agent needs to have strategies for estimating an opponent's utility function by learning the opponent's behaviors since the opponent's utility information is not open to others. However, it is difficult to estimate an opponent's utility function for the following reasons: (1) Training datasets for estimating opponents' utility functions cannot be obtained. (2) It is difficult to apply the learned model to different negotiation domains and opponents. In this paper, we propose a novel method of estimating the opponents' utility functions using boosting based on the least-squares method and nonlinear programming. Our proposed method weights each utility function estimated by several existing utility function estimation methods and outputs improved utility function by summing each weighted function. The existing methods using boosting are based on the frequency-based method, which counts the number of values offered, considering the time elapsed when they offered. Our experimental results demonstrate that the accuracy of estimating opponents' utility functions is significantly improved under various conditions compared with the existing utility function estimation methods without boosting.

Attribute-based encryption (ABE), a cryptographic primitive, realizes fine-grained access control. Because of its attractive functionality, many systems based on ABE have been constructed to date. In such cryptographic systems, revocation functionality is indispensable to handle withdrawal of users, secret key exposure, and others. Although many ABE schemes with various functionalities have been proposed, only a few of these are revocable ABE (RABE). In this paper, we propose two generic constructions of RABE from ABE. Our first construction employs the pair encoding framework (Attrapadung, EUROCRYPT 2014), and combines identity-based revocation and ABE via the generic conjunctive conversion of Attrapadung and Yamada (CT-RSA 2015). Our second construction converts ABE to RABE directly when ABE supports Boolean formulae. Because our constructions preserve functionalities of the underlying ABE, we can instantiate various fully secure RABE schemes for the first time, e.g., supporting regular languages, with unbounded attribute size and policy structure, and with constant-size ciphertext and secret key.